An experiment succeeds twice as often as it fails. The chance that in the next six trials, there shall be atleast four successes is ?->(Show Answer!)

1. An experiment succeeds twice as often as it fails. The chance that in the next six trials, there shall be atleast four successes is

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MCQ->An experiment succeeds twice as often as it fails. The chance that in the next six trials, there shall be atleast four successes is....

MCQ-> Analyse the following passage and provide appropriate answers for the questions that follow: Each piece, or part, of the whole of nature is always merely an approximation to the complete truth, or the complete truth so far as we know it. In fact, everything we know is only some kind of approximation, because we know that we do not know all the laws as yet. Therefore, things must be learned only to be unlearned again or, more likely, to be corrected. The principal of science, the definition, almost, is the following: The test of all knowledge is experiment. Experiment is the sole judge of scientific “truth.” But what is the source of knowledge? Where do the laws that are to be tested come from? Experiment, itself, helps to produce these laws, in the sense that it gives us hints. But also needed is imagination to create from these laws, in the sense that it gives us hints. But also needed is imagination to create from these hints the great generalizations – to guess at the wonderful, simple, but very strange patterns beneath them all, and then to experiment to check again whether we have made the right guess. This imagining process is so difficult that there is a division of labour in physics: there are theoretical physicists who imagine, deduce, and guess at new laws, but do not experiment; and then there are experimental physicists who experiment, imagine, deduce, and guess. We said that the laws of nature are approximate: that we first find the “wrong” ones, and then we find the “right” ones. Now, how can an experiment be “wrong”? First, in a trivial way: the apparatus can be faulty and you did not notice. But these things are easily fixed and checked back and forth. So without snatching at such minor things, how can the results of an experiment be wrong? Only by being inaccurate. For example, the mass of an object never seems to change; a spinning top has the same weight as a still one. So a “law” was invented: mass is constant, independent of speed. That “law” is now found to be incorrect. Mass is found is to increase with velocity, but appreciable increase requires velocities near that of light. A true law is: if an object moves with a speed of less than one hundred miles a second the mass is constant to within one part in a million. In some such approximate form this is a correct law. So in practice one might think that the new law makes no significant difference. Well, yes and no. For ordinary speeds we can certainly forget it and use the simple constant mass law as a good approximation. But for high speeds we are wrong, and the higher the speed, the wrong we are. Finally, and most interesting, philosophically we are completely wrong with the approximate law. Our entire picture of the world has to be altered even though the mass changes only by a little bit. This is a very peculiar thing about the philosophy, or the ideas, behind the laws. Even a very small effect sometimes requires profound changes to our ideas.Which of the following options is DEFINITLY NOT an approximation to the complete truth?
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MCQ-> Study the following information to answer the given questions. A word and number arrangement machine when given an input line of words and numbers rearranges them following a particular rule in each step. The following is an illustration of input and rearrangement. ‘’(All the numbers are two digits numbers and are arranged as per some logic based on the value of the number)’’. Input : win 56 32 93 bat for 46 him 28 11 give chance. Step I : 93 56 32 bat for 46 him 28 11 give chance win Step II : 11 93 56 32 bat for 46 28 give chance win him Step III: 56 11 93 32 bat for 46 28 chance win him give Step IV: 28 56 11 93 32 bat 46 chance win him give for Step V: 46 28 56 11 93 32 bat win him give for chance Step V: 32 46 28 56 11 93 win him give for chance bat and Step VI is last step of the arrangement of the above input as the intended arrangement is obtained. As per the rules followed in the above steps, find out in each of the following questions the appropriate steps for the given input, Input for the questions: Input : ‘’fun 89 at the 28 16 base camp 35 53 here 68’’ (All the numbers given in the arrangement are two digit numbers.)Which of the following would be the Step II?
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MCQ-> Study the following information to answer the given questions: A word and number arrangement machine when given an input line of words and numbers rearranges them following a particular rule in each step. The following is an illustration of input and rearrangement.(All the numbers are two-digit numbers and are arranged as per some logic based on the value of the numbers.) Input:win 56 32 93 bat for 46 him 28 11 give chance Step I:93 56 32 bat for 46 him 28 11 give chance win StepII:11 93 56 32 bat for 46 28 give chance win him Step III:56 11 93 32 bat for 46 28 chance win him give Step IV:28 56 11 93 32 bat win him give for chance bat Step V:46 28 56 11 93 32 bat win him give for chance Step VI:32 46 28 56 11 93 win him give for chance bat Step VI is the last step of the arrangement the above input. Input for the question: Input:fun 89 at the 28 16 base camp 35 53 here 68 (All the number given in the arrangement are two digit numbers.)Which of the following would be step II ?
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MCQ-> People are continually enticed by such "hot" performance, even if it lasts for brief periods. Because of this susceptibility, brokers or analysts who have had one or two stocks move up sharply, or technicians who call one turn correctly, are believed to have established a credible record and can readily find market followings. Likewise, an advisory service that is right for a brief time can beat its drums loudly. Elaine Garzarelli gained near immortality when she purportedly "called" the 1987 crash. Although, as the market strategist for Shearson Lehman, her forecast was never published in a research report, nor indeed communicated to its clients, she still received widespread recognition and publicity for this call, which was made in a short TV interview on CNBC. Still, her remark on CNBC that the Dow could drop sharply from its then 5300 level rocked an already nervous market on July 23, 1996. What had been a 40-point gain for the Dow turned into a 40-point loss, a good deal of which was attributed to her comments.The truth is, market-letter writers have been wrong in their judgments far more often than they would like to remember. However, advisors understand that the public considers short-term results meaningful when they are, more often than not, simply chance. Those in the public eye usually gain large numbers of new subscribers for being right by random luck. Which brings us to another important probability error that falls under the broad rubric of representativeness. Amos Tversky and Daniel Kahneman call this one the "law of small numbers.". The statistically valid "law of large numbers" states that large samples will usually be highly representative of the population from which they are drawn; for example, public opinion polls are fairly accurate because they draw on large and representative groups. The smaller the sample used, however (or the shorter the record), the more likely the findings are chance rather than meaningful. Yet the Tversky and Kahneman study showed that typical psychological or educational experimenters gamble their research theories on samples so small that the results have a very high probability of being chance. This is the same as gambling on the single good call of an advisor. The psychologists and educators are far too confident in the significance of results based on a few observations or a short period of time, even though they are trained in statistical techniques and are aware of the dangers.Note how readily people over generalize the meaning of a small number of supporting facts. Limited statistical evidence seems to satisfy our intuition no matter how inadequate the depiction of reality. Sometimes the evidence we accept runs to the absurd. A good example of the major overemphasis on small numbers is the almost blind faith investors place in governmental economic releases on employment, industrial production, the consumer price index, the money supply, the leading economic indicators, etc. These statistics frequently trigger major stock- and bond-market reactions, particularly if the news is bad. Flash statistics, more times than not, are near worthless. Initial economic and Fed figures are revised significantly for weeks or months after their release, as new and "better" information flows in. Thus, an increase in the money supply can turn into a decrease, or a large drop in the leading indicators can change to a moderate increase. These revisions occur with such regularity you would think that investors, particularly pros, would treat them with the skepticism they deserve. Alas, the real world refuses to follow the textbooks. Experience notwithstanding, investors treat as gospel all authoritative-sounding releases that they think pinpoint the development of important trends. An example of how instant news threw investors into a tailspin occurred in July of 1996. Preliminary statistics indicated the economy was beginning to gain steam. The flash figures showed that GDP (gross domestic product) would rise at a 3% rate in the next several quarters, a rate higher than expected. Many people, convinced by these statistics that rising interest rates were imminent, bailed out of the stock market that month. To the end of that year, the GDP growth figures had been revised down significantly (unofficially, a minimum of a dozen times, and officially at least twice). The market rocketed ahead to new highs to August l997, but a lot of investors had retreated to the sidelines on the preliminary bad news. The advice of a world champion chess player when asked how to avoid making a bad move. His answer: "Sit on your hands”. But professional investors don't sit on their hands; they dance on tiptoe, ready to flit after the least particle of information as if it were a strongly documented trend. The law of small numbers, in such cases, results in decisions sometimes bordering on the inane. Tversky and Kahneman‘s findings, which have been repeatedly confirmed, are particularly important to our understanding of some stock market errors and lead to another rule that investors should follow.Which statement does not reflect the true essence of the passage? I. Tversky and Kahneman understood that small representative groups bias the research theories to generalize results that can be categorized as meaningful result and people simplify the real impact of passable portray of reality by small number of supporting facts. II. Governmental economic releases on macroeconomic indicators fetch blind faith from investors who appropriately discount these announcements which are ideally reflected in the stock and bond market prices. III. Investors take into consideration myopic gain and make it meaningful investment choice and fail to see it as a chance of occurrence. IV. lrrational overreaction to key regulators expressions is same as intuitive statistician stumbling disastrously when unable to sustain spectacular performance.....